Faculty For Mathematical Sciences and Computational Logic

Track: Mathematical
Science & Computational Logic

Location: Sonepat,
NCR of Delhi.

Mode: Full Time,
On Campus

Programme: B. Tech
CS and Data Science

ABOUT US

Rishihood
University       

Rishihood
University (RU) has been established under The Haryana Private Universities
(Amendment) Act, 2020 and is empowered to award degree as specified in section
22 of UGC Act, 1956. 

Rishihood
University is India’s first and only impact university. ‘Impact’ is the living
spirit of Rishihood. The purpose of education envisioned by the thought leaders
of our civilization and that which has motivated the founders to build
Rishihood University is beyond just awarding degrees and jobs. The purpose of
education is to achieve the highest potential in a learner i.e., Rishihood.
Rishihood University provides a unique mix of globally relevant education that
is rooted in Indian ideas, quality education that is affordable, and a
multi -disciplinary exposure with cutting edge skills of a specialist. To
achieve this outcome, education cannot be limited to within the classrooms. RU
is a fully residential campus where living and learning seamlessly integrate
throughout the day. RU faculty and learners have an active participation with
society, industry, researchers, entrepreneurs, and policy makers. This keeps
the learning at RU focused on solving the biggest challenges faced by humanity
and prepares our learners for the real world. It is time India builds
universities driven by a higher purpose, that have a strong committed board to
back it, that redefine the way education is imparted both within and outside
the classroom. Rishihood is a bold initiative to fulfill this idea.
Hence, we are looking for like -minded founding faculty members at Rishihood
University.

About Us

Track | Mathematical
Sciences

Foundation
Mathematics   •   Linear Algebra and Statistics   •  
Applied Optimization for Data Science

Most students
arrive afraid of math. Not because it is hard, but because nobody ever showed
them what it is for. If you have felt the joy of a clean proof and wanted to
give that to someone else, if you have ever explained why gradient descent
works and watched someone's face change, this role was written for you.

You will join Rishihood
as a Faculty who will be responsible for one of the most structurally important
tracks in the programme. Mathematics at SASTech is not a prerequisite you power
through. It is a language you learn to think in. As you grow into the Track
Lead role, you will architect the four year mathematical curriculum, coordinate
across the ML and CS Foundations tracks, and mentor junior faculty to teach
math the way it was meant to be taught.

Requirements

 Key Responsibilities

• Teach Foundation Mathematics, Linear
  Algebra, Statistics, and Applied Optimization across the four year
  programme
  
• Design coursework where every concept
  arrives with a reason, linking calculus to optimization, probability to
  inference, linear algebra to how neural networks actually work
  
• Run labs where students implement
  optimization algorithms from scratch in Python or MATLAB, not just run
  them
  
• Coordinate with the ML and CS track
  leads to sequence math modules intelligently across semesters
  
• Mentor junior faculty to teach
  mathematics as a computational, applied discipline rather than a rote one
  

Job Specifications

You should hold an
M.Tech, Ph.D., or equivalent in a relevant field. Beyond the degree, here is
what we care about.

Technical Depth

• Expert command of linear algebra
  (vector spaces, SVD, PCA), advanced statistics (Bayesian inference,
  inferential statistics), and optimization theory (convex optimization,
  stochastic processes)
  
• Computational fluency in Python
  (NumPy, SciPy), R, or MATLAB; ability to link every topic to its
  downstream application in data science, cryptography, or simulation
  

The Person

• A genuine love of mathematics, not
  just as a tool but as a way of thinking; ability to find the right analogy
  that makes an abstract concept land
  
• Comfort collaborating across
  disciplines and intellectual honesty: you model how to find out what you
  do not yet know
  

Good to Have

• PhD in Applied Mathematics,
  Statistics, or Computational Sciences with a focus on ML or algorithmic
  complexity
  
• Published research in mathematical modelling,
  industry background in quantitative finance, actuarial science, or data
  science research
  

This job
description is not intended to be all -inclusive. The employee may be expected
to perform other duties as assigned by the supervisor.